The theory of composition in physics


Hardy, L. (2013). The theory of composition in physics. Perimeter Institute. https://pirsa.org/13040121


Hardy, Lucien. The theory of composition in physics. Perimeter Institute, Apr. 16, 2013, https://pirsa.org/13040121


          @misc{ pirsa_13040121,
            doi = {10.48660/13040121},
            url = {https://pirsa.org/13040121},
            author = {Hardy, Lucien},
            keywords = {Quantum Foundations},
            language = {en},
            title = {The theory of composition in physics},
            publisher = {Perimeter Institute},
            year = {2013},
            month = {apr},
            note = {PIRSA:13040121 see, \url{https://pirsa.org}}

Lucien Hardy Perimeter Institute for Theoretical Physics


We develop a theory for describing composite objects in physics. These can be static objects, such as tables, or things that happen in spacetime (such as a region of spacetime with fields on it regarded as being composed of smaller such regions joined together). We propose certain fundamental axioms which, it seems, should be satisfied in any theory of composition. A key axiom is the order independence axiom which says we can describe the composition of a composite object in any order. Then we provide a notation for describing composite objects that naturally leads to these axioms being satisfied. In any given physical context we are interested in the value of certain properties for the objects (such as whether the object is possible, what probability it has, how wide it is, and so on). We associate a generalized state with an object. This can be used to calculate the value of those properties we are interested in for for this object. We then propose a certain principle, the composition principle, which says that we can determine the generalized state of a composite object from the generalized states for the components by means of a calculation having the same structure as the description of the generalized state. The composition principle provides a link between description and prediction.